<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Direct on StorageNews</title><link>https://storagenews.top/tags/direct/</link><description>Recent content in Direct on StorageNews</description><generator>Hugo</generator><language>en</language><lastBuildDate>Mon, 16 Mar 2026 00:00:00 +0000</lastBuildDate><atom:link href="https://storagenews.top/tags/direct/index.xml" rel="self" type="application/rss+xml"/><item><title>Ctera Fusion Direct stops AI storage bottlenecks</title><link>https://storagenews.top/posts/ctera-fusion-direct-stops-ai-storage-bottlenecks/</link><pubDate>Mon, 16 Mar 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/ctera-fusion-direct-stops-ai-storage-bottlenecks/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">U. S. Patent 12,007,952 backs &lt;strong>CTera Fusion Direct&lt;/strong>, a system eliminating file-to-object conversion bottlenecks.&lt;/p>
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&lt;p class="std-text">The era of maintaining disjointed NAS silos alongside separate object repositories is over, primarily because the latency they introduce is fatal to modern AI training clusters. &lt;strong>CTera Fusion Direct&lt;/strong> establishes a &lt;strong>federated data architecture&lt;/strong> that allows files and objects to coexist natively within a single global namespace, removing the need for costly data duplication or proprietary chunking schemes. This approach finally delivers the promised convergence of human collaboration protocols and machine-scale throughput without the traditional performance.&lt;/p></description></item><item><title>Direct Databricks access stops ETL copy loops</title><link>https://storagenews.top/posts/direct-databricks-access-stops-etl-copy-loops/</link><pubDate>Tue, 03 Mar 2026 00:00:00 +0000</pubDate><guid>https://storagenews.top/posts/direct-databricks-access-stops-etl-copy-loops/</guid><description>&lt;meta charset="utf-8">
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&lt;p class="std-text">MinIO&amp;#039;s March 3, 2026 launch eliminates the need for complex ETL pipelines by enabling direct Databricks access to on-premises datasets. &lt;strong>AIStor Table Sharing&lt;/strong> fundamentally rejects the outdated necessity of duplicating critical data into cloud storage to satisfy analytics workloads. By embedding the &lt;strong>Delta Sharing&lt;/strong> protocol directly within the storage layer, this architecture solves the persistent friction of &lt;strong>data gravity&lt;/strong> that plagues hybrid AI deployments.&lt;/p></description></item></channel></rss>